class_docstr: *VoxCeleb1* :cite:`nagrani2017voxceleb` dataset for speaker identification task.
  
  Each data sample contains the waveform, sample rate, speaker id, and the file id.
  
  Args:
      root (str or Path): Path to the directory where the dataset is found or downloaded.
      subset (str, optional): Subset of the dataset to use. Options: ["train", "dev", "test"]. (Default: ``"train"``)
      meta_url (str, optional): The url of meta file that contains the list of subset labels and file paths.
          The format of each row is ``subset file_path". For example: ``1 id10006/nLEBBc9oIFs/00003.wav``.
          ``1``, ``2``, ``3`` mean ``train``, ``dev``, and ``test`` subest, respectively.
          (Default: ``"https://www.robots.ox.ac.uk/~vgg/data/voxceleb/meta/iden_split.txt"``)
      download (bool, optional):
          Whether to download the dataset if it is not found at root path. (Default: ``False``).
  
  Note:
      The file structure of `VoxCeleb1Identification` dataset is as follows:
  
      └─ root/
  
       └─ wav/
  
       └─ speaker_id folders
  
      Users who pre-downloaded the ``"vox1_dev_wav.zip"`` and ``"vox1_test_wav.zip"`` files need to move
      the extracted files into the same ``root`` directory.
code: def __len__(self) -> int:
      return len(self._flist)
  
imports: import os
  from pathlib import Path
  from typing import List, Tuple, Union
  from torch import Tensor
  from torch.utils.data import Dataset
  from torchaudio._internal import download_url_to_file
  from torchaudio.datasets.utils import _extract_zip, _load_waveform
label_desc: Use image node_id 4 for calling the VoxCeleb1Identification obj's underlying member method code with example usage: obj.__len__() and returns: len